The Loveland Blog

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August Parcel Data Update

By Sahana Murthy on August 10, 2020 · How-To

Dear Friends of Loveland Parcel Data and,

A lot of important information in this one!
A summary of updates in July of 2020 and the upcoming pipeline is below. 

Key Data Stats:

  • Total parcel age down by 3.5% from last month
  • Average parcel age - 196 days, down from 205 last month
  • Average county age - 215 days, down from 239 last month
  • ~903K new parcels, 71 new counties added & 146 counties refreshed since last month

Land Based Classification System (LBCS) Use Codes update:
We now have over 70% of our parcels with an LBCS code.

Readable LBCS code descriptions - new columns: 
Added the description for each code to every parcel. 

Shapefile Important Information:
Starting this month we have made the following changes to help flag the counties whose data exceeds the 2GB soft limit. Please double check how you are handling these files.

Duplicate Parcel Records:
We are in the process of identifying and removing about 218,000 truly duplicated parcel records across our dataset. Many counties 'stack' parcels to record multiple owners or multiple units, natural resource rights, etc. These situations are expected and they are still considered good data. As a result, these stacked parcels are not affected.

However, we have found a number of parcel records that are actual duplicates, with nothing unique or different between them in any way aside from the 'll_uuid' we assigned each duplicate record.

We will be removing those in August and exporting the corrected counties (918) in September. About 40 counties account for most of the duplicates, and 800 had less than 1% affected parcels. 

We are not sure what caused the issue, but we will put monitoring in place to determine if these are duplicates in the sources or something else is happening to cause them.

USPS Vacancy, Residential indicators:
Now updated monthly. Updated in July 2020, next update in August.

Coverage Report:
Updated for this month and available here:

For all full dataset customers, the updated data is available for download to bulk data clients in these formats: GeoPKG .gpkg (suggested), GeoJSON, Shapefile, and Postgres SQL files.  In addition, this data has been updated on the website.

If your organization uses a custom export we are updating your data at the moment and if you don’t see the latest updates, please drop us a line.

A Data Dictionary for the Loveland Standard Schema is always available here:

A machine-readable version of this list is included in the `verse` table available in all the formats above as well as CSV format for use in spreadsheets. To find the latest updates in verse, sort by 'last_refresh' and use the 'filename_stem' column to identify the file.

Data refreshed or added from the county in July and live now:
( Asterisk * indicates newly added county)
Alabama - Houston

Arizona- Apache, Cochise, Coconino, Gila, Graham, Greenlee, La Paz, Maricopa, Mohave, Navajo, Pima, Pinal, Santa Cruz, Yavapai, Yuma

California - Glenn, Mendocino, San Benito, San Francisco

District of Columbia - Washington

Georgia (55 new counties) - Appling*, Baker*, Banks*, Barrow*, Bleckley*, Butts*, Calhoun*, Candler*, Catoosa*, Chattahoochee*, Chattooga*, Clay*, Clinch*, Colquitt*, Decatur*, Dodge*, Dooly*, Early*, Elbert*, Emanuel*, Franklin*, Glascock*, Hancock*, Harris*, Hart*, Heard*, Jasper*, Jefferson*, Jenkins*, Johnson*, Lamar*, Lanier*, Madison*, Marion*, Meriwether*, Miller*, Montgomery*, Morgan*, Oconee*, Peach*, Pickens*, Pike*, Quitman*, Rabun*, Schley*, Spalding*, Stewart*, Taliaferro*, Tattnall*, Terrell*, Toombs*, Towns*, Treutlen*, Twiggs*, Upson*, Walker*, Walton*, Warren*, Wayne*, Webster*, Wheeler*, Wilkinson*, Worth*, Baldwin, Ben Hill, Brantley, Dade, Evans, Gilmer, Grady, Greene, Laurens, Lee, Lincoln, Long, Lumpkin, Mitchell, Pulaski, Randolph, Rockdale, Seminole, Stephens, Talbot, Taylor, Ware, White, Whitfield 

Illinois - Adams, Crawford, DeKalb, Effingham*, Hancock, Lee, Menard, Pike, Sangamon, Tazewell, Whiteside

Indiana - Grant, Porter

Louisiana - Ouachita

Massachusetts - Barnstable, Berkshire, Bristol, Dukes, Essex, Franklin, Hampden, Hampshire, Middlesex, Nantucket, Norfolk, Plymouth, Suffolk, Worcester

Michigan - Allegan, Arenac, Charlevoix, Cheboygan, Eaton, Emmet, Grand Traverse, Ingham, Ionia, Iron, Jackson, Kent, Lapeer, Leelanau, Lenawee, Marquette, Midland, Montcalm, Muskegon, Newaygo, Oceana, Ottawa, Roscommon, Saginaw, St. Clair, Tuscola, Washtenaw

Missouri - Andrew, Atchison, Bates, Benton, Buchanan, Camden, Christian, Cooper, Dallas, Douglas*, Franklin*, Henry, Holt, Laclede*, Lafayette, Lawrence, Lincoln, Linn, Macon*, Miller, Moniteau, Morgan, Phelps, Ralls, Ray, Vernon, Warren

North Dakota - Billings, Bottineau, Bowman*, Burke, Burleigh, Cass, Cavalier, Divide, Dunn, Emmons, Foster*, Golden Valley, Grant, Hettinger, LaMoure, McHenry, McKenzie, McLean, Morton, Mountrail, Nelson*, Pembina, Renville*, Richland, Rolette, Sargent*, Sheridan*, Sioux, Stark, Steele, Traill, Walsh, Ward, Williams

Nebraska - Arthur, Box Butte

New York - Cortland, Genesee, Madison*, Tioga

Oklahoma - Pottawatomie*

Oregon - Columbia, Umatilla

Pennsylvania - Indiana*, Union, Venango*

South Dakota - Aurora, Beadle, Bennett, Bon Homme, Buffalo, Campbell, Clark, Codington, Custer, Davison, Day, Deuel, Douglas, Edmunds, Fall River, Faulk, Grant, Gregory, Hamlin, Hanson, Hutchinson, Jackson, Jerauld, Jones, Kingsbury, Lake, Lawrence, Lincoln, Lyman, Marshall, McPherson, Meade, Mellette, Miner, Minnehaha, Moody, Oglala Lakota, Pennington, Roberts, Sanborn, Tripp, Union, Yankton

Tennessee - Shelby

Texas - Ochiltree

Wisconsin - Adams, Ashland, Barron, Bayfield, Brown, Buffalo, Burnett, Calumet, Chippewa, Clark, Columbia, Crawford, Dane, Dodge, Door, Douglas, Dunn, Eau Claire, Florence, Fond du Lac, Forest, Grant, Green, Green Lake, Iowa, Iron, Jackson, Jefferson, Juneau, Kenosha, Kewaunee, La Crosse, Lafayette, Langlade, Lincoln, Manitowoc, Marathon, Marinette, Marquette, Menominee, Milwaukee, Monroe, Oconto, Oneida, Outagamie, Ozaukee, Pepin, Pierce, Polk, Portage, Price, Racine, Richland, Rock, Rusk, Sauk, Sawyer, Shawano, Sheboygan, St. Croix, Taylor, Trempealeau, Vernon, Vilas, Walworth, Washburn, Washington, Waukesha, Waupaca, Waushara, Winnebago, Wood

In the current pipeline for updating in August 2020
Michigan - Balance of state
New York - Balance of state

In the pipeline for updating in September


Based on feedback and county challenges, pipeline planning is always subject to change. As always, please contact us if you have any questions about accessing or using the data, if you find issues with any of our data, or you have any comments or questions about our data in specific areas or states. We also love to hear from you about which counties or regions you’d like to see us update next, as it helps inform our planning process.

Thank you for being a part of Loveland!

Happy Mapping!



Statewide Georgia Data & Upcoming Product Launches

By Sahana Murthy on August 5, 2020 · Announcements

We are gearing up for a few product announcements coming up later in August and September.
So we are going to keep our August update fairly short. :)
Digging in:

1. Statewide Georgia Data:

We are happy to announce that we now have parcel data for all of Georgia state. If you are looking for statewide GA, please reach out to us at While we had some of GA until now, being able to add the rest of the state has surely been a major milestone for us.
If you are looking for individual counties in GA, then the Landgrid data store would be the place to do to for instant downloads of county data in the format of you choice -

It wasn't just GA that we updated, we recently improved and increased our coverage in MI, ND and are soon looking to add the missing counties in OK as well. 
We are working our way towards reaching complete nationwide data coverage, hopefully by the end of 2020. :)

2. Upcoming Product Announcements:

Landgrid Data API & Tileserver - Self-serve SaaS subscriptions

We recently launched our raster & vector Tileserver as its own stand alone product. Thank you to those who reached out asking for more information on it. We are currently working on making our API & Tileserver subscriptions entirely self-serve like our other SaaS subs - the Data Store and the Landgrid Pro & Team subs. Soon you will be able to pick and choose the API subscription tier that suits your needs best and be on your way to using our API and/or tiles instantly, without any delays. 
Stay tuned, the launch is coming soon. 

Landgrid Pro & Bookmarking on the Landgrid mobile App
We are bulking up our Landgrid mobile app with a comprehensive set of new features.

Soon, you will be able to sign up and use Landgrid Pro straight out of the app and use the same login for the web version as well. Not just that, we are bringing some of our most killer features, including bookmarking properties to the mobile app. 
So you will not only be able to look up properties on the go, but you will be able to bookmark them, add notes to your favorite properties and even take pics of properties that are of most interest to you on the app.

The list doesn’t just stop there. You will soon be able to manage & work on surveys straight out of the app too, along with enjoying some of our pro map layers like buildings footprints & more. 

Phew--- Now that’s a big product update! So, stay tuned, the launch is coming soon. 

3. Upcoming Webcast:
We have an amazing webcast coming up this Friday, August 7th at 3 PM with Kevin Ehrman-Solberg from Mapping Prejudicean organization that has been doing amazing work mapping racial covenants (restrictions written into deeds that barred non-whites from purchasing the property) and their impacts in Minneapolis and beyond.

Join us live as we sit down to chat with Kevin about racial covenants, data & how crowdsourcing has been critical to gathering this data. We're big fans of Mapping Prejudice here at Loveland, and we encourage all of you to join in and participate.

Register at this link to save your spot for the webinar -

In addition to talking about Mapping Prejudice's innovative work crowdsourcing data on racial covenants in Minneapolis, we'll discuss how data has historically been used both as a vehicle for and an ally against racism over time, what currently available data indicates about the state of the nation, as well as what the future may hold.

That’s it from us for now. Please be on the lookout for some launch emails & communications from us. 
Until then, enjoy the rest of your summer.

Please stay safe & well and as always, feel free to reach out to us at for all parcel data & mapping information. Or to just say “hi” :)

Happy Mapping!

Team Loveland


The New Landgrid Tileserver, API limits and Much More!

By Sahana Murthy on July 9, 2020 · Announcements


Hope you all had a nice, long 4th of July weekend.
We are back with some updates for you on this hot summer day! 

1. Launching the Landgrid Tileserver: Make beautiful maps with our raster & vector tiles. 

Use our raster (PNG) and vector (MVT) tiles to show parcel boundaries on your Leaflet, Mapbox, or ESRI baselayer. Our tiles come with parcel polygons and the identifiers you need to look up additional details with our search API.

This is the same service we use across our platform and mobile apps, ready for use at scale in your tools. We keep it up-to-date with the latest parcel updates so your clients always see the freshest data.
If you are interested in using our Tileserver, please email us at and we can set you up in no time.

You can learn about the pricing tiers and limits for our tileserver here -

We will soon make this a self-serve subscription so you pick & choose the tier you want and sign up for it and get instant access to our tiles. 

2. API usage limits:
We are introducing new limits on the API tiers, based more on the output than number of requests. We didn’t want to limit API calls or requests for our customers. However, we do have generous output limits now in place for the three API tiers as shown below.

3. Updated Parcels page:
We recently gave our parcel bulk data page a little spruce up. It was due for an update. You know why??? Because our parcel data has gotten bigger, better, and robust in the past year as you may have noticed from our monthly data stats and updates. :) 

Check it out -

We want to showcase more of our customers on this page. Let us know if you are interested in telling your Landgrid data story by emailing us at
We want to celebrate your work , product & project.

4. Podcasts and webcasts:

If you have been following us and our content, then you probably know that we have been pretty busy making interesting videos, webcasts and featured podcasts. Here’s the list of some of our most recent podcasts:

1. Polygons of Ownership - The Mapscaping Podcast
Mapscaping recently featured our CEO - Jerry Paffendorf on their podcast where they discussed parcel data and how our land is divided and sub-divided into polygons. 

Catch the full podcast and interview here -

Android -

2. The Talking Grid with Pivvot - Location with Context

We recently hosted the the amazing team of Pivvot on our webcast. Catch this fun conversation about Pivvot, data, data trends & COVID on our Youtube channel and website.

That was the July update folks. 
Exciting things are coming soon this quarter, so stay tuned with us.

As always, please feel free to email us at if you have any questions or would like to discuss an idea with us. We are always available to chat. 
Until next time, have a wonderful rest of your July.  

Happy Mapping!

Polygons of Ownership (Mapscaping Podcast Featuring Jerry Paffendorf)

By Sahana Murthy on July 7, 2020 · Democratizing Data

"The below is a cross-post of the Mapscaping blog on the podcast they did recently with our CEO - Jerry Paffendorf on land parcels, how our landgrid is divided & sub-divided & why parcel data is fundamental to decision making. The Mapscaping article is linked here.

You can also listen to the full podcasts here:

Android -




Jerry Paffendorf is the CEO and co-founder of Loveland Technologies. On their, they map out the world for all to see how it is subdivided, owned, inhabited, and used in the form of land parcels.



It’s the subdivision of property boundaries that cover the US, numerous other countries, and ultimately, the Earth. 

Property is surrounded by a legal space that the government defined and sectioned off to the owner with a street address for tax purposes.  It’s a polygon, rectangle, or square space. A host of other information is connected to that parcel, such as when it was first subdivided, is there a structure on it, and does it have utility hookups?  What are the permissions, zoning, and taxes owed on it? 

Someone put a boundary of space around this area, defined it, subdivided the land, permitted ownership to it, and then allowed it for occupancy uses.  It’s a giant crossword puzzle superimposed on the US and certain other parts of the world.  This is what parcel data is.




In the US, the data is gathered and stored with county assessors, around 3,100 of them nationwide.  The assessor is someone at the county level who is responsible for managing the taxation, ownership, and similar information.  This is generated and rolled up from individual villages, towns, and cities.  It’s usually stored and updated independently, for example, with varying column names and degrees of enthusiasm to share it or not.  It’s public information, and as you can imagine, with these many parties doing things differently, sometimes it’s readily available, and sometimes it costs money to get it.  

We take all that parcel data from every county and put it into a common schema, which is then organized, updated, and automated to the highest degree possible, and it becomes a seamless fabric. You can do analysis and work across different counties or states because it’s easy to digest.




The data is factual. It comes from the local government, and we add additional columns that are not typically available from the same authority, such as buildings data. Is there a building on this parcel? What is the size of the building? Occupancy data from the US Postal Service helps with determining if the building is occupied or not.

We also assign a nationwide land-use code to each parcel.  In addition to local zoning, which is sometimes unavailable, this helps in determining what kind of land it is.  Farming, urban, or commercial? These fields are continually evolving, and we keep them up to date. 

Often, our partners and customers who use this data have property or location data but not a parcel.  Now they can enrich their data with ownership particulars, legal boundaries, zoning, occupancy details, and addresses. Companies get more insights from these combined data sets.



The possibility is vast.

Our parcel data is foundational; it’s basic, legal information—address, land use, ownership, and subdivision.

It’s rudimentary, but nevertheless very insightful.  If you’re an insurance company and you have a list of current customers, you can now improve your risk modeling by including boundaries, ownership, or other fields in your model.

If you’re the creator of a hunting or outdoor recreation app, you’ll need to know if you have permission to access the land where you’re planning to go.

Real estate users combine our data and add the number of rooms or indicate a swimming pool that the property may have. They use this for sale prices and valuation models or for a history of ownership and mortgages.

Some people use it for geocoding location data onto a map or for machine learning models for changes in the temperature that affect sea-level rise for a particular area.

Recently, we joined a consortium of data companies that provide free data for doing research and response to COVID-19. It’s headed by a company, SafeGraphthat focuses on consumer points of interest, and provides information on consumer expenditure and foot traffic. The data comes from apps where people gave permission to show their location and is then used for COVID-19 research efforts.

Our parcel data can also be useful in simple cases, such as asking permission to create a garden on a vacant plot or even sending a letter to the owner to make them aware of something.  All the pieces of land are owned and controlled by someone who is accountable for them and can be spoken to about something that’s happening there.





MapBox saw use in our parcel data.  They help people place stuff accurately on a map based on addresses or latitude and longitude points. Parcel data that comes with addresses, as well as centroids in the middle of that polygon, can help position other kinds of data in the right place. In their case, they’re not interested in zoning, owners, taxes, or structures.  They need an address and a physically bounded box that they can attach other data to and put it on the surface of the Earth more accurately and rapidly.  We are happy to be a piece of the geocoding stack.




Our data is factual. You can’t make it up. It’s not a case of someone looking at a house and claiming that a woman named Jennifer owns this.  We work with facts from deeds to determine lot lines, the year the structure was built, or its assessed value.  This information can be appended to that polygon, right to that parcel. To get to that point, you need to overlay it on top of different kinds of imagery or data that may not be structured similarly.

I’m really big on what the short-term possibilities are for taking that frame of a polygon, the frame of the parcel, and using it to crop super high-resolution imagery.  Then you have a picture frame drawn around the surface of the Earth.  What’s inside the picture frame?  Grass, trees, buildings, cars, and activities.  Now you can describe what’s in the frame to the system with human language.

Essentially there are 150 million land parcels that make up the US. That’s 150 million pictures with frames that need filling with data and imagery.  Teach the software to the best you can what’s inside a frame, repeat a few thousand times, and you can run that over a much larger number of parcels. 

We are only beginning to scratch the surface of this, and we can already see exciting work being done. 

Those who deal with change detection on parcels, for example, need time-stamped aerial imagery from different dates.  They want to see if there is a building or a tree in the way. Combining parcel data with imaging and other types of differently structured data is in the internal test phase, and we are creating the right partnerships. 

We’ve got government facts which we’ve enhanced with other, privately assembled data and then added computer vision and some training. There is a lot you can do with this, even getting derivable insights about our planet.

Sometimes, all people need is a bit of parcel data to find the missing piece of what they’re working on that’s not as legible as they need it to be to understand properties and yards.




It is, particularly, for the impacts of climate change or sea-level rise. 

First Street Foundation does cutting edge modeling for climate change, sea-level rise, and the effects on coastal communities. Data scientists and geospatial experts might be looking at what’s the temperature in the atmosphere in a given area.  How’s that correlating to ice melting?  How’s that relating to the rise in the water?  Where is the water going to spill over?  How far above or below sea level?

Someone will then go and decide what all that means for actual people and property or municipal costs. If the water goes in this far, what will be the damage?  How many properties will it cover?  What are those properties?  Houses, businesses, or institutional structures?  What are the values of these buildings? Someone might have to decide on what will go into helping people to move if that’s necessary.  Or incentivize residents to move to higher ground if that was deemed necessary by a local government. 

For scientific, geological, or hydrological research, parcel data isn’t necessarily the set that you would grab first.  But when you need to know the practical effects of an impact on a place, you’ll want our data at some point. Only then you’ll know how many people might be affected if this or that happens, and you might even need to get down to specifics, like ownership. This is how parcel data becomes relevant to climate change.




It is.  But don’t take my word for it. Andro Linklater wrote two books on the subject of land. 

Owning the Earth is a historical overview of the land ownership regimes that different people, nations, and civilizations have applied.  It’s an array from God owns everything, and the King/Queen/Pharaoh owns everything to our hybrid systems in the US, which is a more extreme version of private property.

Measuring Americais about how the land grid came into existence.  Jefferson sent a group of surveyors around to subdivide space into square miles around 1790. They dragged 66-foot long metal chains through the woods, over prairies, mountains, and across rivers.  They kept careful track of every square mile section, made notes on it, and gave it an identifier. 

The idea was that every six by six square mile section could be set apart as a township and they set aside a square mile for public use of lands and education.  These townships would snap together into counties and states.  This was the thinking in the late 1700s. 

There was this massive land, all that space.  They wanted to create a coherent framework for it to be inhabited with residents.  At the time, those plots were not developed organically, they were anomalous, so someone had to go and layout this grid.

Descriptions of these square mile parcels were brought to Washington DC, Philadelphia, New York, and auctioned off to the highest bidder.  They were then further subdivided over time and became counties and states and reached a certain population.  It’s the boundaries of that square mile survey that still subdivide and give boundaries to our city streets.  Some parts of California and Texas did things differently. Nevertheless, from the Ohio-Pennsylvania border to the West and the North, you’ll find the imprint of the surveyors’ chain. 

Since then, we’ve taken the grid for granted, and it’s more or less fixed and permanent. There isn’t much talk of changing or flexing it, andMeasure America never even considered Native Americans and indigenous people who were originally occupying the land. It was just laid out on top of a way of life that was here previously. Should the grid change and adapt to modern living patterns and the economy, allow for nature and conservation efforts?

Once you see the land grid, it gets you thinking. How could it be modified or used differently? What do you need to initiate change, and where do you even start?  My guess is you start with group decisions and politics.




We started mapping parcels in Detroit, Michigan. At the time, there were many issues in the city, and the population was at its peak, three times the current number.  There were a lot of vacant buildings and land to serve people better, people were losing their properties over not being able to pay over-assessed taxes, systematic racism and a diminished tax base were present with less than helpful neighbors. 

One place that we saw where we could be useful is to illuminate the land grid.  We built our business on figuring out whatshould exist, then how we can fund it, grow it, and provide reliable service.

In the future, someone should create a global repository for all subdivisions of space that humans are superimposed on, from countries down to individual buildings. The population of the planet has expanded hugely to around 8 billion, and we need to start managing resources and the quality of life by understanding how the Earth is owned, used, and occupied.  What gets measured gets improved. It would take multiple lifetimes just to expand our data set and extend it to other places, figure out what issues people care about, and start to address them to make life better. 

Of course, I can see issues with access and politics.  Different views, cultures, power dynamics make this global vision a challenge.  But it’s not entirely hopeless if you look at Wikipedia or OpenStreetMap. They are public, and people have access to them to understand things. 

I’m thinking, in the future, what else can we add to something like them that would be similarly useful for people and life? 

Everyone carries a smartphone around with them these days and – like it or not – you’re broadcasting yourself, and you’re trackable.  Your location and activities are present on the grid. Someone is watching from space, and you’re in this mirror world situation.  Governments and people will have to decide what works and what’s still comfortable, and I can see how this land grid is going to be part of that.  It’s coming, and it’s either going to be built with a public sphere to it, or it will be quietly assembled by private actors and not very accessible.  I’m trying to make moves that help our parcel data fit into this picture. 

For now, my focus is on obtaining government facts, making the data easy to plug into, more accessible and affordable for people than it’s ever been before. Prioritizing people and projects and go by what feels right and fair

We can help everyone: the curious resident, map makers, and organizations who need lots of stuff.  Whatever you need, you’ll find something valuable using our free parcel viewer, GIS tools, or a land grid mobile app.


I, for one, was surprised to learn about Jefferson’s square mile survey back in the late 1700s. Did you go and look up the book on Amazon?  I did. Do mirror worlds scare you, or you look forward to seeing some real-life sci-fi happening, and it got you thinking about that phone in your pocket?  I’d love to hear your thoughts. 

Be sure to subscribe to Mapscaping's podcast for weekly episodes that connect the geospatial community.